Sentence examples for model the reading from inspiring English sources

Using this model, the reading, organization and interpretation of data does not come from a fragmentation of texts but from a more global view, keeping in mind the context in which data were generated.

This method was based on a negative binomial distribution model; the read count of gene i in the sample of j was designated Kij.

For our own model the reads were aligned using segemehl.

We used both the negative binomial and the normal distribution to model the read count data.

We model the read counts with the negative binomial distribution after correcting for the effect of genomic deadzones.

The Poisson distribution has been widely used to model the read count feature of RNA-seq and ChIP-seq data.

In order to do so, we need a probabilistic model of the reading order in case of a natural reading behavior.

Khalifa and Weir (2009) proposed a comprehensive model of the reading process that addresses the role of readers' cognitive operations to enable an empirical investigation of cognitive processing complexity in reading.

The edgeR algorithm models the read counts associated to a gene using a negative binomial probability distribution.

This test for differential expression in RNA-Seq data models the read counts mapping to a given repeat family using a negative binomial distribution with the parameters estimated from the observed data.

Our model incorporates the read information in a probabilistic model through base quality scores within each read.